{"id":"W2085486672","doi":"10.1145/507072.507084","title":"What do the eyes behold for human-computer interaction?","year":2002,"lang":"en","type":"article","venue":"","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Human–computer interaction; Eye tracking; Usability; Desk; Eye movement; Cursor (databases); Computer vision; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001127238,0.0000868328,0.00008345591,0.00006067859,0.0002202776,0.0004704418,0.0007475848,0.00004521991,0.00008086044],"category_scores_gemma":[0.000007289841,0.00005411506,0.00006667411,0.0001265147,0.00005377337,0.0005543909,0.0001408854,0.0001146734,0.0001098581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001474248,"about_ca_system_score_gemma":0.000002193994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005894626,"about_ca_topic_score_gemma":0.00001097107,"domain_scores_codex":[0.9993379,0.00001839569,0.0001214543,0.0002568613,0.00008301131,0.0001824198],"domain_scores_gemma":[0.999306,0.0001352151,0.00004508785,0.0004432979,0.00004886843,0.00002150573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[9.067115e-7,0.0001126593,0.0004282786,0.000005162885,0.00002656451,0.00000352064,0.000494135,0.00003759302,0.0003228668,0.4656553,0.0434308,0.4894822],"study_design_scores_gemma":[0.001657053,0.001045477,0.01519637,0.0001817311,0.00003814719,0.0001673197,0.001028324,0.2796673,0.01641622,0.1002148,0.5833146,0.001072644],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02958811,0.0002243342,0.9470828,0.01772814,0.001728063,0.0002028665,5.043952e-7,0.000626949,0.002818194],"genre_scores_gemma":[0.9781436,0.00002448862,0.01822744,0.0009842087,0.0001349792,0.00003282876,4.352384e-7,0.000005517586,0.002446494],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9485555,"threshold_uncertainty_score":0.4536481,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05126503547248688,"score_gpt":0.2979151869949846,"score_spread":0.2466501515224977,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}